There are a variety of approaches to track a location of an individual based on global positioning system (GPS) data. However, GPS often does not work reliably in an environment with weak or unreliable GPS data. Therefore, there is increasing interest in developing new techniques to provide location-based services.
Trajectory data may be generated using information generated by a user's mobile device, where the mobile device can take different forms depending on the location based service. As an example, trajectory data may be calculated using pedestrian dead reckoning (PDR) based on information generated from the user's mobile device without relying on conventional RF infrastructure such as Wi-Fi networks or Bluetooth beacons. As examples, an accelerometer or magnetometer (compass) on the mobile device may be used to generate information to perform pedestrian dead reckoning.
Trajectory data using PDR has been widely used for indoor tracking and positioning for individuals. Given a start point with an initial known location, such as a GPS coordinate, an indoor localization system can track a user's current position using indoor trajectory data by estimating the number of steps and direction of movement.
Another application of trajectory data using PDR is understanding indoor activity patterns of users. Indoor trajectory data collected from users is an important data source for activity pattern analysis. For example, how often a user moved in a shopping mall and how long he stayed in front of a shopping shelf may indicate the users' shopping interests and contextual information. Aggregating indoor trajectory data from multiple users may help a store owner to find out problems of shelf arrangement. The store owner may use the data to improve arrangement for improving user's shopping experience, and gaining store profit.
Another application of trajectory data using PDR is indoor mapping. Indoor trajectory data may be use to map an indoor environment. In turn, the generated maps can be used for indoor location based services.
However, a problem with calculating trajectory data using PDR is that many mobile devices, such as smartphones, have significant compass noise and gyroscope noise. Thus, even if an initial accurate location was available, there is noise in any subsequent PDR calculation based on the smartphone's sensor data. For example, FIG. 1A shows a floor plan and a path used for indoor trajectory data collection. FIG. 1B illustrates two trajectories 110 and 120 based on two rounds of PDR data calculation. The indoor trajectories are not well overlapped because of the noise in the smartphone's gyro and compass. In particular, the initial heading of the indoor trajectories have a drift and the angle of each corner on the two trajectories is slightly different.
Another problem with conventional PDR is the different start points of trajectories. Referring to FIG. 2A, suppose two different instances of trajectory data are acquired. The data may be acquired for two paths that largely (but not completely) overlap and which have different starting points. For example, two different individuals in an office may have different cubicles (different starting points) but may otherwise navigate certain common segments of the indoor locations. In any case, the initial starting points of each instance may be different and the paths do not have to be identical. As illustrated. In the most general case the starting points are offset. The fact that there are different starting points, combined with gyro and compass errors, has the result that the two trajectories may be totally mismatched when plotted in the same coordinate system, as illustrated in FIG. 2B for traces 205 and 210. This is a fundamental problem for most indoor trajectory based location systems.
Various existing solutions improve accuracy and permit matching different paths typically require prior knowledge of trajectories or information manually provided by users such that the techniques are not fully automatic. For example, some approaches require special training data, the identification of landmarks, or special Bluetooth nodes.
Therefore, in view of these problems the present invention was developed.